Does this mean this is just a research project that Uber doesn't actually use in their cars yet?

From https://eng.uber.com/sbnet/

"By applying convolutional neural networks (CNNs) and other deep learning techniques, researchers at Uber ATG Toronto are committed to developing technologies that power safer and more reliable transportation solutions."

"CNNs are widely used for analyzing visual imagery and data from LiDAR sensors. In autonomous driving, CNNs allow self-driving vehicles to see other cars and pedestrians"

There are many projects using deep learning with lidar. Google PointNet, PointNet++, also https://www.youtube.com/watch?v=UXHX9kFGXfg . These are all much newer than 2D CNNs and I don't know if it works well enough to actually be used in SDCs. Also, using CNNs on point clouds comes with all sorts of problems.

I was really hoping I wouldn't need to be the first person to point this out! Thanks Jeff

My understanding is that you don’t do analysis or training inside the control loop at all. Basically, build a model and then it becomes a go/no-go check when you really want to use it.